Instructions to use SummerChiam/rust_image_classification_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SummerChiam/rust_image_classification_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SummerChiam/rust_image_classification_2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("SummerChiam/rust_image_classification_2") model = AutoModelForImageClassification.from_pretrained("SummerChiam/rust_image_classification_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SummerChiam/rust_image_classification_2: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/SummerChiam/rust_image_classification_2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SummerChiam/rust_image_classification_2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SummerChiam/rust_image_classification_2/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 4812733a4f61cf6d13c50565df6dbb68c16504f257c96f1d75cafd9bef07aa9c
- Size of remote file:
- 343 MB
- SHA256:
- e0b65637a71748abd44e8fe5397c75591d47e7fdeec8943c7c19cd5256b4b49a
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